Search Results for author: Mathieu Seurin

Found 8 papers, 2 papers with code

Don't Do What Doesn't Matter: Intrinsic Motivation with Action Usefulness

1 code implementation20 May 2021 Mathieu Seurin, Florian Strub, Philippe Preux, Olivier Pietquin

Sparse rewards are double-edged training signals in reinforcement learning: easy to design but hard to optimize.

reinforcement-learning

A Machine of Few Words -- Interactive Speaker Recognition with Reinforcement Learning

no code implementations7 Aug 2020 Mathieu Seurin, Florian Strub, Philippe Preux, Olivier Pietquin

To do so, we cast the speaker recognition task into a sequential decision-making problem that we solve with Reinforcement Learning.

Decision Making reinforcement-learning +2

HIGhER : Improving instruction following with Hindsight Generation for Experience Replay

no code implementations21 Oct 2019 Geoffrey Cideron, Mathieu Seurin, Florian Strub, Olivier Pietquin

Language creates a compact representation of the world and allows the description of unlimited situations and objectives through compositionality.

Language Acquisition

I'm sorry Dave, I'm afraid I can't do that, Deep Q-learning from forbidden action

no code implementations4 Oct 2019 Mathieu Seurin, Philippe Preux, Olivier Pietquin

Violating constraints thus results in rejected actions or entering in a safe mode driven by an external controller, making RL agents incapable of learning from their mistakes.

Industrial Robots Q-Learning

Self-Educated Language Agent with Hindsight Experience Replay for Instruction Following

no code implementations25 Sep 2019 Geoffrey Cideron, Mathieu Seurin, Florian Strub, Olivier Pietquin

Language creates a compact representation of the world and allows the description of unlimited situations and objectives through compositionality.

Language Acquisition

Visual Reasoning with Multi-hop Feature Modulation

1 code implementation ECCV 2018 Florian Strub, Mathieu Seurin, Ethan Perez, Harm de Vries, Jérémie Mary, Philippe Preux, Aaron Courville, Olivier Pietquin

Recent breakthroughs in computer vision and natural language processing have spurred interest in challenging multi-modal tasks such as visual question-answering and visual dialogue.

Question Answering Visual Dialog +2

Unsupervised state representation learning with robotic priors: a robustness benchmark

no code implementations15 Sep 2017 Timothée Lesort, Mathieu Seurin, Xinrui Li, Natalia Díaz Rodríguez, David Filliat

We reproduce this simplification process using a neural network to build a low dimensional state representation of the world from images acquired by a robot.

Representation Learning Transfer Learning

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